GPS Moving Performance on Open Sky and Forested Paths

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GPS Moving Performance on Open Sky and Forested Paths

Yoichi Morales and Takashi Tsubouchi

Abstract In this paper we present a systematic study ofthe performance of seven different configurations of GPS on amoving vehicle using three different GPS receivers. The sevendifferent configurations are 1)single frequency code differentialDGPS, 2)double frequency code differential DGPS, 3)RTK-GPSreceiving RTCM correction from a mobile phone, 4)RTK-GPSreceiving RTCM correction information via wireless modulefrom base antenna, 5)StarFire WADGPS, 6)StarFire-DGPSdual mode and 7)StarFire-RTK GPS dual mode. As GPS ismostly used in loosely coupled configurations where receiveroutput is fused with other sensors, the contribution of this paperis the statistical comparison in two dimensions of different GPSconfigurations using as performance index availability, precision(using standard deviation parameters of each measurement)and reliability. Two types of study environments were tested,

open sky and under tree shading. Time for re-acquiring fixsolution for RTK-GPS configurations and re-acquiring dual fre-quency solution by dual frequency configurations are discussedas well. Finally, experimental measurement results show howunder tree shading, biased position data with small covariancecan be rejected thresholding measurements with small HDOPvalues and large number of satellites used for solution.

I. INTRODUCTION

A. Research Motivation

According to Japans Ministry of Internal Affairs and

Communications [1], forests occupy 64.8% of the total area

of the country and about 73% of Japans territory is moun-

tainous. For this reasons, autonomous vehicle localizationand navigation has to address the issues of mountainous

forested environments. Our research motivation is the au-

tomation of construction vehicles in woodland mountain en-

vironments. The final goal is the achievement of autonomous

navigation in such environments where a reliable and robust

localization system is crucial. Our research objective is

to develop a robust localization system. We consider that

the first step to achieve such objective is testing sensor

performance through tree foliage environments that present

not optimal conditions. As GPS is widely used for outdoor

localization, in this paper we report our systematic analysis

of different GPS receivers in different configurations.

B. Related Works

Outdoor localization is a major task for many fields such as

mapping, vehicle navigation and automation. One of the most

commonly used sensors for outdoor navigation is GPS. It is

known that GPS performance decreases close to or under tall

This work has been supported by the Japan Society of Promotion ofScience (JSPS) Grant-in-Aid for Scientific Research (Scientific Research(B)) under contact number 18360116

Y. Morales and T. Tsubouchi are with Graduate School of Systems andInformation Engineering University of Tsukuba, Tsukuba, 305-8573, Japan(yoichi,tsubo)@roboken.esys.tsukuba.ac.jp

obstacles, Martin et al. (2000) in [2] reported the effects of

peripheral tree canopy on DPGS performance on forest roads

finding a relation between DOP1 and percentage of open

sky, T. Yoshimura et al. (2003) in [3] made a precision and

accuracy comparison of GPS positioning in many types of

Japans forested areas in three dimensions, J. Rodriguez et al.

(2006) in [4] made a comparison of accuracy and precision

of four different GPS receivers in different Spanish forest

canopy covers giving recommendations for their use. In

previously cited works, experiments were done in stationary

conditions where antenna was fixed in a determined position.

It has also been addressed by Ohno et al. (2004) in [5]

and Morales et al. (2007) in [6] that even though RTK-GPSis the most precise GPS system, for a moving vehicle in

real time applications where tall structures such as buildings

and trees may exist around GPS antenna, DGPS offers

the most robust performance. Lately, with the appearance

of Wide Area Differential GPS (WADGPS) systems such

as StarFire, it becomes possible to achieve high accuracy

without the necessity of having a base station close to GPS

receiver. Moreover, the availability of receivers being able to

operate in dual mode configurations where receiver switch

seamlessly to the most precise solution available, expands the

fields to be investigated on GPS. Therefore, in this paper we

present a systematic statistical comparison of seven different

types of GPS in single and dual modes placed on a mobilevehicle evaluated under open sky and a tree foliage path.

A brief description of DGPS configurations and GPS types

of noise will be presented in the next subsections.

C. Code Differential GPS (DGPS)

Differential GPS was created to correct bias errors of the

user receiver using measured bias errors at a known position.

A base station computes corrections for each satellite signal

and sends it to the user by a radio link. DGPS uses C/A2

code for positioning and is mainly composed of 3 elements,

one GPS receiver(antenna) at a known location (named base

station), one GPS receiver at an unknown location (user

receiver) and a communication medium between this tworeceivers. Base Station and user receiver have to be within

a distance of 100 km and need at least 4 common satellites

in view. Precision of single frequency DGPS receivers is

within 1 meter and modern double frequency receivers within

1DOP Dilution of Precision is a unitless measure of the magnitude oferror in GPS position fixes due to the orientation of the GPS satellites withrespect to the GPS receiver. DOP is provided by GPS as output in NMEAformat. There are different DOPs to measure different components of theerror (GDOP,PDOP, HDOP, VDOP,TDOP)

2C/A Coarse Acquisition code or civilian code is the pseudo random codegenerated by GPS satellites

Proceedings of the 2007 IEEE/RSJ InternationalConference on Intelligent Robots and SystemsSan Diego, CA, USA, Oct 29 - Nov 2, 2007

ThA11.4

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20 cm (double frequency receivers can practically eliminate

ionospheric refractions). DGPS can correct error sources

with the exception of multi-path.

D. Real Time Kinematic GPS (RTK-GPS)

Real Time Kinematic GPS can provide centimeter accu-

racy measurements in real time. User antenna needs to be

within a distance of 10km to the base station for receiving

real time radio links for position correction. It uses C/A code

and carrier phase for position calculation. RTK needs initial-

ization time of about 1 minute in order to give maximum

precision. RTK offers two types of solutions, float and fix.

RTK float solution needs at least 4 common satellites and

offers an accuracy within 1m. RTK fixed solution needs

at least 5 common satellites for initialization and offers

accuracy within 2cm.

E. StarFire Differential GPS System

StarFire is a global DGPS system developed by NAVCOM

Technology, Inc and Ag Management Solutions, it provides

sub-decimeter horizontal positioning. In order to obtain high

accuracy, StarFire is based on a technology called RTG (Real

Time GYPSY) developed by the Jet Propulsion Laboratory

(JPL) for the National Aeronautics and Space Administration

(NASA) [8], [9], [10]. The system is constituted of seven

components: reference network, processing hubs, commu-

nication links, land earth stations, geostationary satellites,

monitors and dual frequency user receivers.

F. GPS Types of Noise

J. Huang et al. in [7] classified DGPS noise characteristics

from a moving vehicle in four types. On this study we add

a fifth type of noise as shown below:

1) Noise type 1: Stationary noise with clear statisticalproperties due to ionospheric and tropospheric delays.

2) Noise type 2: Non stationary noise due to satellite

geometric distribution.

3) Noise type 3: Multipath or sudden data jumps due to

tall structures around receiver antenna.

4) Noise Type 4: Blockage or lack of GPS output when

there is not enough satellites information to perform a

positioning solution.

5) Noise Type 5: Data jumps caused because of the

change of fix quality in GPS solution. This is the case

of the change between single frequency and double

frequency measurements or the change between RTK

float and fixed solutions.The rest of the paper is organized as follows: Section

II gives a description of GPS receivers used, Section III

present experimental setup and evaluation indexes, Section

IV presents experimental results, conclusions and future

works are presented on Section V. The next section provides

a brief description of used GPS receivers.

II. GPS RECEIVERS

The following three GPS receivers were used for perfor-

mance comparison:

A. Trimble DSM12/212 beacon DGPS

Trimbles DSM 12/212 DGPS receiver has 12 L1 C/A

code carrier phase channels, it includes an integrated dual-

channel low noise beacon receiver for differential correc-

tions. Antenna type: Dome.

B. Trimble 5700 RTK-GPS

Trimble 5700 RTK GPS receiver has 24 dual-frequencychannels (L1 C/A Code, L1/L2 Full Cycle Carrier, WAAS

EGNOS3). Antenna type: Zephyr Geodetic

C. NAVCOM SF-2050M

SF-2050M GPS receiver has 26 tracking channels (12

L1/L2 full wavelength carrier phase tracking GPS + 2

dedicated SBAS4 ), C/A P1 and P2 code tracking. It has a

tri-band antenna which can receive GPS and StarFire signals.

This receiver can be used as DGPS, RTK-GPS and StarFire

WADGPS. Moreover in dual mode it can be used as DGPS-

StarFire or RTK-GPS-StarFire where mode changes in a

seamless way to the most precise solution. Antenna Type:

Tri-band Dipole.

III. EXPERIMENTALS ETUP

A. GPS Receivers Configuration

The seven types of GPS configurations that we tested on

this study are listed below:

1) Single frequency code differential DGPS (Trimble

DSM12/212 DGPS).

2) Double frequency code differential DGPS (NAVCOM

SF-2050M with CSI-Wireless SBA-I beacon receiver).

3) RTK-GPS receiving RTCM5 correction information

from a mobile phone (Trimble 5700 RTK).

4) RTK-GPS receiving RTCM correction information viawireless module from base antenna (NAVCOM SF-

2050M with wireless module for CMR6 RTK-GPS

corrections sent from Trimble 5700 RTK used as

reference).

5) StarFire WADGPS (NAVCOM SF-2050M with

StarFire Differential Service).

6) StarFire-DGPS dual mode (NAVCOM SF-2050M

with StarFire Differential Service coupled with CSI-

Wireless SBA-I beacon).

7) RTK-GPS-StarFire dual mode (NAVCOM SF-2050M

with StarFire Differential Service coupled with wire-

less module for CMR RTK-GPS corrections sent from

Trimble 5700 RTK used as reference).In the seven different configurations for all measurements,

GPS receivers were configured with the following parame-

ters:

3EGNOS European Geostationary Navigation Overlay Service is a Euro-pean satellite system used to augment the GPS and GLONASS systems

4SBAS Satellite Based Augmentation System is a general term whichencompasses WAAS, StarFire and EGNOS type corrections

5RTCM Radio Technical Commission for Maritime Services is a standardformat for Differential GPS corrections used to transmit corrections from abase station to rovers

6CMR Compact Measurement Record

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Satellites required for solution: 4 Solution mode: 3D Max PDOP: 5 Logging rate: 1Hz Antenna height on mobile vehicle: 1.70mWe used information calculated on real time of each

receiver using output format NMEA 01837. We used GGA in

NMEA format for position information and quality indicatorand GST as well for measurement standard deviation infor-

mation. GSA in NMEA format is also used for Dilution of

Precision (DOP) parameters. As GPS provides information in

latitude and longitude coordinates, for this study, we realized

coordinate conversion according to Japanese Geographical

Survey Institute (JGSI) [11]. The origin of our coordinate

system is situated at 139500E in Longitude and 3600Nin Latitude which is referenced as coordinate system IX of

the JGSI.

Fig. 1. Traversed path in bird view. Parking lot with tree canopy passagesegment B-C in blue. (http://www.roboken.esys.tsukuba.ac.jp/ yoichi/Map)

B. Experiment Environment

Measurements were done on March 26th 2007 at 19:00

hours in a clear sky day at Tsukuba Universitys parking

lot and woodland path next to it located at Lat. 36o06.11N

and Lon. 140o05.91E (WGS-84 coordinate system). Exper-

imental path is shown on Figure 1 which is a satellite picture

taken from google earth API (trajectory was drawn by hand,

segments A-B and C-A represent open sky and segment B-

C is under tree foliage). GPS receivers were placed on a

fixed spot on a Yamabico mobile robot platform, shown in

Figure 2. Start position was selected to be an obstacle freeenvironment. After receivers were initialized and receiving

fix measurements, mobile platform was manually pushed

starting from point A moving to point B, then under tree

canopy path from point B to C, finally ending on open

field returning to start point A. Route followed by robot

was previously measured in stand still mode by Trimbles

5700 RTK-GPS in fixed solution (precision within 2 cm).

Under tree shading, a straight line was marked using a

7NMEA National Marine Electronics Association specifications for GPSoutput text format

laser range finder where points of the line were carefully

measured in stand still mode in fixed solution by RTK-

GPS. This measurements were used as ground truth for all

experiments. Line segment B-C under tree foliage has a

length of 78.18m. A picture of the environment under tree

shading with the marked line in blue is shown on Figure

3. Each experiment with in each configuration was done 10

times one after another following the same path. Because

measurements were done at different times, GPS satellite

geometry was different from each experiment, however,

because of previous experimental results experience, it is

considered that performance tendency of each configurations

is maintained.

Fig. 2. Yamabico Platform Mobile Robot with GPS Receiver and Antenna

Fig. 3. Ground truth path under tree shading marked with blue plastic tape

C. Evaluation Index

In order to evaluate and compare GPS performance, threeparameters were used: 1)Measurements availability percent-

age, 2)Measurements precision and 3)Measurements reliabil-

ity percentage. These parameters are defined as follows:

1) Availability:Availability is the percentage of time that

a system is performing a required function under stated

conditions [12]. For this study, we define GPS availability

as the percentage of time when the GPS receiver performs

positioning measurements with its standard deviation pa-

rameters, i.e., receiving GGA and GST in NMEA sentence

format. According to GPS receivers settings, position data

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is determined every second, however, because of not enough

satellites or blockage of differential correction, sometimes

there is no output available (noise type 4). As duration of

experiment is known (time is given by GPS receiver) as

well as the number of data we expect (in this case one

measurement per second), we can determine availability as

defined in the next expression:

Availabilit y(%) = NDR

NDE100 (1)

where NDR is the number of data received (position with

standard deviation) and NDE is the number of expected data.

2) Precision: Precision refers to the closeness of the

observations to the observation sample mean. To calculate

precision index, we used standard deviation provided by GST

sentence (GPS output specified in NMEA format) of each

configuration as shown on equation 2:

H=

DR

i=1

x2i+y2i

NDR(2)

where the average H is the precision index and NDRis the number of data received (position with its standard

deviation).

3) Reliability:As defined in [12], reliability is the prob-

ability that a service, when it is available, performs a

specified function without failure under given conditions for

a specified period of time. Reliability was only calculated for

measurements under tree shadings. The process to determine

reliable data is as follows:

First the perpendicular distance from a point measured

by GPS to the real traversed straight line path d =|AxGPS+ByGPS+C|

A2+B2was used to determine intersection

point PR which is considered to be the position point on

the real path (see Figure 4 for reference). It was assumed

that point PR is the real position of the robot on the real

path line.

2a2b

Real Path Traversed(Ground Truth Line)

d

PRPosition on the Real Path

(XGPS,YGPS)Position Estimated

by GPS (GGA)

Positions CovarianceEllipse (GST)

Ax+By+C=0

Fig. 4. Real path line, estimated position and its covariance ellipse

In order to measure reliability of measurements under

trees, we counted the number of points PR on the real line

path that satisfied the 95% confidence level provided by GPS.

The GST sentence provides covariance ellipse parameters

semi major axis a, semi minor axis b and the angle of

rotation of the ellipse as well as standard deviation values.

Two standard deviations (2 ) were used to determine what

points satisfy the 95% confidence condition which is defined

as follows:

xR2

(2a)2+

yR2

(2b)2 < 1 (3)

Then reliability is defined as:

Reliabil ity(%) =NRE

NDR100 (4)

whereN REis the number of points PR satisfying the 95%

confidence level (condition of expression (3)) and NDR is the

number of data received (position with standard deviation).

Through this performance index, we can detect the amount of

data that because of multipath effects (noise type 3) presents

a wrong position out of 95% confidence value.

Fig. 5. StarFire-DGPS dual mode positioning data with its covarianceellipses. Double Frequency in red and Single Frequency in blue

IV. EXPERIMENTALR ESULTS

In this section we present and discuss our experimental

results. Figure 5 shows the result of one run test showingposition and covariance ellipses measured by StarFire-DGPS

dual mode configuration. Double frequency DGPS fixed

measurements are plotted in red, single frequency DGPS

fixed measurements in blue points and fixed not valid points

in pink. 2 covariance ellipses are plotted in cyan. It can

be appreciated how double frequency measurements with

small covariance ellipses were locked for some seconds

after entering forested path. Then solution changed to single

frequency measurements showing bigger covariance ellipses

until the end of the run. On the next subsections, for each

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evaluation index, average results of 10 running tests in each

configuration are presented.

A. Availability Results

Availability percentage results are shown on table I where

it can be seen that in open sky all configurations offered

excellent availability. Under forested path, configuration 1

offered the best performance followed by configurations 2

and 6, where all configurations were a type of beacon DPGS.

GPS Configuration Availability (%)Open Sky Tree Canopy

1)Trimble DGPS 99.93 99.18

2)NAVCOM DGPS 99.06 96.92

3)Trimble RTK 99.12 91.21

4)NAVCOM RTK 99.08 90.18

5)StarFire 99.04 81.05

6)StarFire-DGPS 99.04 94.66

7)StarFire-RTK 99.05 91.39

TABLE I

AVAILABILITY PERCENTAGE RESULTS IN OPEN SKY AND UNDER TREES

B. Precision Results

Precision results and HDOP average values are shown on

table II. On this table we can see how RTK-GPS configura-

tions 4, 7 and 1 respectively presented the best precision

index in open sky (the smallest the precision index the

most precise measurements are). However, under tree canopy,

beacon DGPS configurations 1, 2 and 6 presented the best

precision index.

GPS Configuration Open Sky Tree CanopyPrecision HDOP Precision HDOP

1)Trimble DGPS 1.39 0.93 1.46 0.932)NAVCOM DGPS 1.95 1.50 1.83 2.31

3)Trimble RTK 1.27 1.12 9.44 4.66

4)NAVCOM RTK 0.07 1.19 3.49 2.05

5)StarFire 1.66 1.40 9.15 3.35

6)StarFire-DGPS 1.94 1.49 3.23 2.33

7)StarFire-RTK 0.19 1.28 6.21 2.66

TABLE II

PRECISION IN OPEN SKY AND UNDER TREES

C. Reliability and Data Selection Results

From data taken in forested path, there were some data

that because of effects of noise type 3 present non consistentmeasurements, i.e., position points out of the traversed line

whose covariance ellipses do not include the real traversed

line segment as shown on Figure 6 (some grey crossed points

with HDOP>4 and number of satellites < 5).

It is known that GPS is more precise when there is

a larger number of satellites and good angular separation

between. HDOP is the acronym of horizontal dilution of

precision which is a parameter of horizontal accuracy of GPS

depending on satellite geometry. During periods of optimal

performance, HDOP values should be under 5. After GPS

measurements analysis and trying different combinations of

parameters, we found that if only measurements with HDOP

values equal or under 4 and if number of satellites used for

solution was set to 5 or more, then number of biased position

measurements not satisfying 95% confidence level decreased

increasing the reliability percentage (non consistent measure-

ments were removed). Figure 7 shows how biased points

(grey points on Figure 6) could be removed from the plot

graph.

Fig. 6. StarFire-DGPS dual mode configuration: position data withcovariance ellipses under tree shading

Fig. 7. StarFire-DGPS dual mode configuration: position data with HDOPvalues under 4 and 5 or more satellites used for solution

Reliability results are shown on table III where it can be

seen and increase in reliability percentage of thresholded data

in all GPS configurations compared, where again DGPS bea-

con configurations 1 and 2 offered the best performance. It

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has to be mentioned that obviously, as reliability percentage

of data available increases, availability percentage decreases

because of data rejection. Also, configuration 1 presented

excellent availability and reliability results, however reliabil-

ity results were favorable because this receiver outputs big

standard deviations in all its measurements.

GPS Configurati on Reli abi lit y (%)

All Data Thresholded Data1)Trimble DGPS 100.00 100.00

2)NAVCOM DGPS 83.63 93.82

3)Trimble RTK 91.82 92.36

4)NAVCOM RTK 87.67 88.82

5)StarFire 82.89 93.99

6)StarFire-DGPS 83.92 92.45

7)StarFire-RTK 81.46 84.94

TABLE III

RELIABILITY RESULTS UNDER TREES WITHOUT AND WITH DATA

SELECTION

D. High Precision Mode Reacquisition TimesUnder tree foliage environments, GPS configurations 2,5

and 6 fell from double frequency to single frequency mea-

surements and configurations 3,4 and 7 lost RTK fixed

solution measurements. We measured double frequency reac-

quisition times for configurations 2,5 and 6 and RTK fixed

solution reacquisition time for configurations 3,4 and 7.

Results listed on table IV show how configurations 4 and

7 (NAVCOM SF-2050M) reacquired fixed measurements

almost ten times faster than configuration 3 (Trimble 5700).

For configurations 2, 5 and 6, it took about 80 seconds to

regain double frequency measurements. An observed issue

of double frequency measurements re-acquirement, was that

a data jump of within 1 meter was produced (noise type 5).Position data after jump offers big covariance information

which slowly decreases with time until maximum precision

is reacquired.

GPS Configuration Time (seconds)

2)NAVCOM DGPS 80.88

3)Trimble RTK 125.60

4)NAVCOM RTK 9.90

5)StarFire 89.10

6)StarFire-DGPS 85.60

7)StarFire-RTK 13.55

TABLE IV

AVERAGE REACQUISITION TIMES AFTER TREE BLOCKAGE

V. CONCLUSIONS AND FUTURE WORKS

In this paper we presented our systematic statistical analy-

sis of GPS moving measurements in open sky and under tree

shading environments. From experimental results, robustness

of beacon DGPS configurations 1, 2 and 6 for measure-

ments under tree environments was proved, showing the best

availability, precision and reliability parameters. Even though

not robust under tree foliage, high precision of RTK-GPS

configurations 3, 4 and 7 on open sky environments was

confirmed. These three configurations offered similar results,

where method to receive correction information did not have

a big impact in overall performance. StarFire stand alone

offered excellent availability and precision index for open

sky measurements, however, as it receives correction infor-

mation from a geostationary satellite, it was highly affected

by tree foliage around GPS antenna. StarFire stand alone

performance was improved by dual mode configurations

that can offer the advantages of two GPS solutions on one

receiver. Finally, it was demonstrated how by thresholding

and using position data with HDOP 4 and number ofsatellites5; position measurements reliability increased inall configurations. The importance of increasing reliability

parameter is that when GPS position information is fused in

a kalman filter framework, unbiased observations (unbiased

position data and covariance information) has to be fed

for good filter performance. As future work, GPS moving

measurements in different kinds of forested environments

is left as well as an analysis in 3 dimensions. Moreover,

performance in different types of weather conditions is openfor analysis.

VI. ACKNOWLEDGMENTS

Authors would like to thank Mr. Masayuki Uchida from

GNSS Technologies Inc. for his technical support on GPS.

REFERENCES

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